1,720,971 research outputs found
TESTING A PRECISE HYPOTHESIS INTERPRETING P-VALUES FROM A ROBUST BAYESIAN VIEW POINT (LOWER BOUNDS, POSTERIOR PROBABILITIES)
No full textThe testing of two-sided hypotheses in univariate and multivariate situations is considered. The goal is to establish lower bounds on the posterior probabilities of null hypotheses, using Robust Bayesian techniques, and to compare these lower bounds with the corresponding P-values. The lower bounds are calculated over classes of prior distributions which (1) assign specified probabilities to each hypotheses; and (2) can otherwise be considered to be objective . An example would be the class of all prior distributions which assign probability 1/2 to each hypothesis and are suitably symmetric . Dealing with such classes of priors imbues the lower bounds on posterior probability with an objectivity that is lacking in Bayesian analyses with a specified prior. This objectivity is also indicated by the fact that the results can be interpreted as bounds on the likelihood ratio of the hypotheses, if one were to take a likelihood approach to testing. The interest in these lower bounds, besides their intrinsic Bayesian interest, is that they tend to be considerably larger than the corresponding P-values. While it is well understood that P-values and posterior probabilities are very different quantities the magnitudes of the differences that we observe make clear the need for very careful interpretation of P-values
Lower bounds on Bayes factors for invariant testing situations
No full textAbstractHypothesis testing problems are studied when invariance under suitable groups of transformations exist. Both compact and locally compact groups are considered. Expressions for the lower bounds on Bayes factors are derived under fairly general conditions. It is shown that the lower bounds can be obtained from weighted likelihood ratios of maximal invariants. These lower bounds are then compared with the P-values for these tests. It is found that the lower bounds are usually much larger than the corresponding P-values
Lower bounds on Bayes factors for invariant testing situations
No full textHypothesis testing problems are studied when invariance under suitable groups of transformations exist. Both compact and locally compact groups are considered. Expressions for the lower bounds on Bayes factors are derived under fairly general conditions. It is shown that the lower bounds can be obtained from weighted likelihood ratios of maximal invariants. These lower bounds are then compared with the P-values for these tests. It is found that the lower bounds are usually much larger than the corresponding P-values.hypothesis tests invariance compact topological groups locally compact topological groups maximal invariants Bayes factors posterior probability P-values
Going Beyond Counting First Authors in Author Co-citation Analysis
Get PDFThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Variations on the Author
Get PDF“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Appropriate Similarity Measures for Author Cocitation Analysis
Get PDFWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
Dispelling the Myths Behind First-author Citation Counts
Get PDFWe conducted a full-scale evaluative citation analysis study of scholars in the XML research field to explore just how different from each other author rankings resulting from different citation counting methods actually are, and to demonstrate the capability of emerging data and tools on the Web in supporting more realistic citation counting methods. Our results contest some common arguments for the continued
use of first-author citation counts in the evaluation of scholars, such as high correlations between author rankings by first-author citation counts and other citation
counting methods, and high costs of using more realistic citation counting methods that are not well-supported by the ISI databases. It is argued that increasingly available digital full text research papers make it possible for citation analysis studies to go beyond what the ISI databases have directly supported and to employ more
sophisticated methods
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